1. Field of the Invention
The present invention generally relates to a method to assist senior management decision-making, and to closely monitor various performance measures of an entire enterprise. Specifically, the method relates to extending Supply Chain Management (SCM) using Financial Management (FM) considerations, as well as extending FM using SCM considerations. This is accomplished by employing a more comprehensive approach to maximizing profitability, and increasing revenue, and explicitly considering risk.
2. Background Description
Current methods for supply chain management (SCM) and financial management (FM) practice are incomplete. Supply chain management solutions focus on the goods and information flows, but neglect financial requirements. Financial management solutions focus on financial flows, but do not adequately incorporate supply chain management needs.
Businesses require complete solutions that integrate the supply chain and finance functions. Financial management considerations such as international taxes, foreign exchange risk management expense, and financing choices can be critical to supply chain decisions. Although they have no impact on traditional of supply chain performance measures such as logistics costs and cycle time, these financial management factors go straight to the bottom line, and can have a dramatic impact on a firm""s financial performance. In some cases, companies have developed ad hoc systems linking supply chain management and financial planning activities. However, the effectiveness of these solutions has been constrained by limited sharing of information, and locally optimized decision-making.
The current state of the Supply Chain Management and Financial Management marketplace, the nature of existing software solutions, and the competitive position of key vendors is discussed below. Many academics and practitioners have attempted to bridge the gap between Supply Chain Management and Financial Management, but they have only been partially successful.
Supply Chain solutions operate at three levels:
Execution levelxe2x80x94Enterprise Resources Planning (ERP);
Planning levelxe2x80x94Supply Chain Management (SCM); and
Strategic levelxe2x80x94Strategic Enterprise, Systems (SES).
FIG. 1 shows the evolution of these solutions in the marketplace. Earlier solutions, i.e., circa 1985-1993, consisted of in-house solutions or material requirement planning and distribution requirement planning. These previous methods have failed to use information technology to integrate Supply Chain Management and Financial Management. They have also failed to exploit significant opportunities to improve financial performances by integrating Supply Chain Management and Financial Management. The early to mid-1990""s saw a move to enterprise resource planning consisting of bookkeeping, automating traditional functional activities, and data integration. The late-1990""s saw a further move toward advanced planning systems, or supply chain management which uses sophisticated and xe2x80x9cintelligentxe2x80x9d decision-support systems for different enterprise functions. A Strategic Enterprise Systems (SES), which is the subject of the present invention, does not yet exist in state of the art systems.
The degree of integration in current offerings is very good at the execution level. It spans a wide range of functions, from human resources (HR) to plant operations. However, only sparse integration at the planning level exists, today.
The current trends in business application software development are toward custom software, developed in-house; commercial products marketed by function (scheduling software, accounting software, etc.); integrated suites and niche product. However, a complete integrated solution does not yet exist. Key industry trends include:
De facto linkages between enterprise resource planning (ERP) and SCM where SCM vendors have aligned their applications with dominant ERP systems to facilitate integration;
Vertical Focus where product and marketing strategies focus on market segments and niches;
Increasing industry consolidation through mergers and acquisitions; key ERP vendors are acquiring new expertise and product offerings to enter the lucrative SCM market; but the market is still fragmented; and
Increasing solution integration where ERP vendors are pursuing a product bundling strategy, linking planning and decision support tools with their ERP products, and current industry strategy, according to AMR Research, Inc. of Boston, Mass., calls for vendors to integrate their product suites to serve as backbones to support real-time supply chain decision-making.
ERP systems are currently available from SAP AG of Walldorf, Germany (R/3(trademark)); Oracle Corporation of Redwood City, Calif. (Oracle Discrete Manufacturing, Oracle Flow Manufacturing); Baan Company NV of Hemdon, Va. (BaanERP, Baan Supply Chain Solutions), PeopleSoft, Inc. of Pleasonton, Calif. (PeopleSoft Supply Chain Planning, PeopleSoft Production Management), and J. D. Edwards and Company of Denver Colo. (J. D. Edwards Manufacturing Suite, J. D. Edwards Logistics/Distribution Suite, J. D. Edwards Financial Suite).
SCM systems are currently available from I2 technologies of Irving, Tex. (Rhythm(trademark)), Manugistics Group, Inc. of Rockville, Md. (The NetWORKS(trademark) Solution Set), SAP AG, Oracle Corp. (Oracle Applications Release Financials), Baan Company NV, and ILOG SA of Mountain View, Calif. (ILOG Optimization Suite).
ERP products for Financial Management are available from SAP, Oracle, PeopleSoft, J. D. Edwards, and Baan.
Current accounting solutions are capable of the following:
General Ledgerxe2x80x94Central repository of accounting transactions;
Accounts Receivable and Payablexe2x80x94Tracks customer sales and receipts, and vendor purchases and payments;
Asset Accountingxe2x80x94Tracks fixed assets;
Funds Managementxe2x80x94Tool for planning, managing and monitoring a firm""s funds; and
Activity-based costingxe2x80x94Monitors and controls costs of cross-departmental business processes, functions and products.
Current financial management solutions are capable of the following:
Profitability analysisxe2x80x94Analyzes sources of profits. Revenues are matched with costs by market segment, or other business rules. Critical decision support tool for product pricing, customer selection, targeting distribution channels, etc.;
Corporate-wide budgetingxe2x80x94Investment planning and budgeting for the entire enterprise. Tracks available budgets, and compares planned and incurred costs;
Cash Managementxe2x80x94Provides information on sources and uses of funds to ensure liquidity to meet payment obligations. Supplies data for managing short-term investments and borrowing;
Treasury Managementxe2x80x94Manages the treasury function, including foreign exchange and electronic funds transfers;
Loan Managementxe2x80x94Automates loan-manage process, and tracks interest and repayment terms; and
Risk Managementxe2x80x94A set of tools to monitor and assess risk, usually using value-at-risk measures.
Academic research to date has tended to focus on highly specialized or niche subjects. A vast literature exists on specific supply chain management subjects such as optimizing inventory policies, network design, routing schemes, and resource allocation. There has been an accelerating trend towards applying academic research results to the practice of corporate management. Researchers and practitioners, in particular in the Operations Management/Operations Research (OM/OR) community, have developed a framework, under the rubric of SCM, to link these various fields. Historically, they have focused on the operational side of a company""s activities. From a theoretical standpoint, integration of different aspects of SCM, even on the operations side, is still in its infancy. This is due mainly to a legacy problem: many well known and widely used results would have to be revised to support integration. Furthermore, the mathematical difficulties involved in integration can be non-trivial.
On the finance side, there is a large body of work focusing on topics such as optimal capital structure, cost of capital, hedging methodologies, tax minimization strategies, and depreciation methods. Theoretical linkages between SCM and other fields, such as accounting, corporate finance, international tax law, etc, are not well-established in the academic literature. Some linkages have been proposed, primarily by practitioners, but in a fragmented fashion. Some of the relevant literature that tries to bridge this gap is described below.
Current SCM practice is described in Sridhar Tayur, Ram Ganeshan and Michael J. Magazine, xe2x80x9cQuantitative Models for Supply Chain Management (International Series in Operations Research and Management Science, 17)xe2x80x9d (December 1998, Kluwer Academic Publishers). This book is a collection of papers by leading authorities in the field of supply chain management, each covering one aspect of SCM, and providing extensive references.
Most models in the current literature use MIP (Mixed Integration Program) models for supply chain design. The optimization objective is typically to minimize costs, although some seek to maximize profit. The general modeling approachxe2x80x94and the concomitant obstacles to incorporating foreign exchange riskxe2x80x94are summarized in the following excerpt from a paper by Morris Cohen and Arnd Huchzermeier:
xe2x80x9cThe current state-of-the-art in global manufacturing strategy planning models can be characterized by two fundamental approaches: network flow models and option valuation models. Network flow models exploit primarily portfolio effects within the firm""s global supply chain network. In general, network structure decisions are numerous, but are exercised rather infrequently, e.g., on a periodic base. Alternatively, option value models focus primarily on production switching or sourcing decisions contingent on future states of nature. In general, production options are limited, but can be exercised frequently, e.g. on a continuous basis. The polarization in research is due to the analytical complexities of each modeling approach, i.e. network complexity in the first case and stochastic complexity in the second case. Consequently, there persists a significant gap in the literature on unified modeling approaches for global manufacturing strategy options under exchange risk.xe2x80x9d
See Morris Cohen and Arnd Huchzermeier, xe2x80x9cGlobal Supply Chain Management: a Survey of Research and Applicationsxe2x80x9d, Quantitative Models for Supply Chain Management (Ed. S. Tayur, R. Ganeshan, M. Magazine; Kluwer Academic Press 1999) pp. 669-702.
Several authors have proposed simple models linking SCM to FM. Single-period, deterministic models have been developed by James E. Hodder, xe2x80x9cPlant Location Modeling for the Multinational Firmxe2x80x9d, Proceedings of the Academy of International Business Conference on the Asia-Pacific Dimension of International Business, Honolulu, 1982, M. A. Cohen, M. L. Fisher and R. Jaikumar, xe2x80x9cInternational Manufacturing and Distribution Networks: A Normative Model Framework,xe2x80x9d Managing International Manufacturing (Ed. Kasra Ferdows: North-Holland, Amsterdam: 1989), and M. A. Cohen and H. L. Lee, xe2x80x9cResource Deployment Analysis of Global Manufacturing and Distribution Networks,xe2x80x9d Journal of Manufacturing and Operations Management, Vol. 2, pp. 81-104, 1989. Hodder developed a mixed-integer programming formulation that combines decisions for plant location, resource allocation, and local borrowing. Cohen, Fisher and Jaikumar propose a hierarchical solution procedure for a nonlinear, mixed-integer programming formulations that defines optimal transfer prices as well as resource allocation, production and sourcing decisions.
For a variety of exchange rate scenarios, Cohen and Lee exploit the potential of a firm""s flexible manufacturing and distribution network to balance the firm""s global after-tax profit. All of these formulations do not explicitly allow for randomness and dependencies in the cash flows between locations. Doing this ultimately leads to portfolio effects, which can have a significant impact on a firm""s choice of global manufacturing strategy.
James E. Hodder, xe2x80x9cFinancial Market Approaches to Facility Location under Uncertainty,xe2x80x9d Operations Research, Vol. 32, pp. 1374-1380 (1984), James E. Hodder and James V. Jucker, xe2x80x9cA simple Plant-Location Model for Quantity-Setting Firms Subject to Price Uncertainty,xe2x80x9d European Journal of Operational Research, Amsterdam, Vol. 21, pp. 39-46 (1985), James E. Hodder and James V. Jucker, xe2x80x9cInternational Plant Location Under Price and Exchange Rate Uncertainty,xe2x80x9d International Journal of Production Economics, Vol. 9, pp. 225-229 (1985) and James E. Hodder and C. Dincer, xe2x80x9cA Multifactor Model for International Plant Location and Financing under Uncertainty,xe2x80x9d Computers and Operations Research, Vol. 13, No. 5, pp. 601-609 (1986) adopted a mean-variance objective function. Their proposed problem formulations are based on a multi-factor model for exchange rate determination. However, multi-factor models have performed rather poorly over the period of floating exchange rates.
The model presented in Morris Cohen and Arnd Huchzermeier seeks to maximize the profits of an international company, considering both exchange rate risk and demand uncertainty. They employ a generic model, where uncertainty is captured by expected values.
Issues of ownership structure, fees, royalties etc. are addressed in an early paper by David P. Rutenberg, xe2x80x9cManeuvering liquid assets in a multi-national company: formulation and deterministic solution procedures,xe2x80x9d Management Science, Vol. 16, No. 10, pp. 671-684 (June 1970). This paper represents a partial analysis for tactical planning, since it takes as given the planned operations of each national subsidiary, and hence whether the subsidiary is to be a net source or recipient of funds each year.
Application cases have been reported in P. S. Bender, W. D. Northup and J. F. Shapiro, xe2x80x9cPractical Modeling for Resource Management,xe2x80x9d Harvard Business Review, pp. 163-173 (March-April 1981), in the paper industry; in R. L. Breitman and J. M. Lucas, xe2x80x9cPLANETS: A Modeling System for Business Planning,xe2x80x9d Interfaces, pp. 94-106 (January-February 1987) for the automobile industry; in Cohen and Lee and in B. C. Arntzen, G. G. Brown, T. P. Harrison and L. L. Trafton, xe2x80x9cGlobal Supply Chain Management at Digital Equipment Corporation,xe2x80x9d Interfaces, pp. 69-93 (January-February 1995) for computer assembly. The model of Arntzen et al. builds on the models of Cohen and Lee (1989) and Huchzermeier (1991) by explicitly considering issues such as duty drawbacks and tariffs. Operational hedging is discussed by Panos Kouvelis in xe2x80x9cGlobal Sourcing Strategies under exchange rate uncertaintyxe2x80x9d. Gordon Gilstrap, xe2x80x9cContribution of Logistics and Supply Chain Management to Shareholder Value,xe2x80x9d The Sematech Semiconductor Logistics Forum, November 1999, indicates that in the future there will be linkages between financial flows and other aspects of the supply chain, but provides no further detail.
More recently, the literature has focused on real options in supply chains. Examples of real options are considered, with option values derived in very simple and stylized settings. Supply chain network options differ from project options, because they exploit synergies derived from global coordination of multiple investments, i.e. network design decisions; and from global coordination of sourcing and distribution logistics, i.e. network material flow decisions. This more realistic context has not been considered by the current literature on valuing non-financial options.
There are a number of limitations to the approaches as described above. In particular, they consider only one exchange rate process, they assume a constant dividend rate, they utilize a cost minimization objective rather than an after-tax profit maximization objective, they consider only a few production switching options, and/or they deal only with a single-period production planning problem.
There are currently no models that effectively integrate SCM and FM. In particular, none of the models effectively considers the tight coupling of the production decision with cash flow movements, royalty fees, dividend repatriation, etc.
It is therefore an object of the invention to provide a method to assist senior management decision-making, and to closely monitor various performance measures of an entire enterprise. Specifically, the method relates to extending Supply Chain Management (SCM) using Financial Management (FM) considerations, as well as extending FM using SCM considerations. This is accomplished by employing a more comprehensive approach to maximizing profitability, and increasing revenue, and explicitly considering risk.
Broadly speaking, these integration opportunities enhance traditional supply management techniques in two ways:
1. Employing a more comprehensive approach to maximizing profitability, and increasing revenue. This is accomplished by tightly integrating SCM and FM to exploit opportunities created by dynamically responding to changes in market prices, demand, and foreign exchange rates. Several different approaches can be used. Probably the most promising, at least in the near-term, is to identify new ways to maximize profits by incorporating financial considerations into supply chain management decisions. These considerations include the objective of reducing corporate income taxes, personal property taxes, and dividend withholding taxes, as well as improved utilization of financial assets, such as cash xe2x80x9cinventoriesxe2x80x9d. There are also opportunities to integrate supply chain considerations and techniques into financial management decisions. In particular, by placing greater emphasis on the timing of the receipt of cash inflows, supply chain solutions can improve utilization of financial assets, such as cash and receivables. Finally, the greatest benefits can be gained by simultaneously integrating both supply chain management and financial management.
2. Explicitly considering risk The impact of risk can be assessed in a number of different ways, but probably most important is its affect on funding costs and the firm""s cost of capital. The approach seeks to reduce interest expense by exploiting SCM to expand the firm""s set of financing opportunities, and by improved decision-making. And it seeks to reduce the firm""s cost of capital by reducing sensitivity to a suite of risk factors, including foreign exchange risk, interest rate risk, political risk, catastrophe risk, business risk, counterparty risk, credit risk, and geographic risk.
According to the invention, a strategic business plan is generated to assist decision-making, and to closely monitor various performance measures of an enterprise by extending supply chain management using financial management considerations. The method uses information and models derived from at least one of the following planning processes:
Supply chain managementxe2x80x94designing a supply chain model for a firm utilizing firm-specific information including strategic objectives, a desired level of risk, market position of the firm and industry competitive landscape;
extended demand planningxe2x80x94determining which customer demands to fulfill, and when to fulfill them, while factoring in demand uncertainty, capacity and time constraints;
inventory managementxe2x80x94developing inventory policies to service stochastic customer demand, using information related to service targets, budgets, stock out probabilities and costs and demand fulfillment rates;
procurement planningxe2x80x94mitigating foreign exchange risk by considering the firm""s global foreign exchange position using vendor selection, thereby reducing foreign exchange exposures; and
production planningxe2x80x94dynamically shifting production in coordination with procurement planning to locations with weak currencies, thereby reducing production costs.